language:
- ca
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Medium Catala 1k steps
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: ca
split: test
args: ca
metrics:
- name: Wer
type: wer
value: 10.9688
Whisper Md Ca - 1k This model is a fine-tuned version of openai/whisper-medium on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
Loss: 0.2554 Wer: 10.9688 Model description More information needed
Intended uses & limitations More information needed
Training and evaluation data More information needed
Training procedure Training hyperparameters The following hyperparameters were used during training:
learning_rate: 1e-05 train_batch_size: 32 eval_batch_size: 8 seed: 42 gradient_accumulation_steps: 2 total_train_batch_size: 64 optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 lr_scheduler_type: linear lr_scheduler_warmup_steps: 100 training_steps: 1000 mixed_precision_training: Native AMP
Training results Training Loss Epoch Step Validation Loss Wer 0.2554 1.0 1000 0.2554 10.9688 Framework versions Transformers 4.26.0.dev0 Pytorch 1.13.1+cu117 Datasets 2.7.1.dev0 Tokenizers 0.13.2